Deep Fake Technology and How to Detect It

In January 2024, Americans across the country were caught off guard by a peculiar news story. It all started with a series of robocalls hitting New Hampshire voters, claiming to be from none other than President Biden himself. Imagine getting a call and hearing the familiar voice saying, “What a bunch of malarkey. “Your vote makes a difference in November, not this Tuesday.”

But here’s the twist: it wasn’t Biden at all. The voice on the other end turned out to be artificial intelligence mimicking the president’s voice. This caused quite a stir, with many questioning the authenticity of the calls and the technology behind them. Reports soon revealed that ElevenLabs, the company responsible for the AI voice-cloning software, had taken action by banning the account linked to these calls.

This isn’t the first time the world has been shaken by the power of AI. And trust me, it’s not just one famous face falling victim to deepfake technology. From religious leaders to Ukrainian President Volodymyr Zelenskyy, and even music superstar Taylor Swift, they’ve all had their share of AI-generated imposters. The good news? There are a few tiny tweaks that can help you spot these fakes.

In this blog, we will discuss in detail all about deep fakes, and I’ll share some handy tips and tricks to help you tell the real deal from AI-generated frauds.

What is Deep Fake Technology?

Deepfake technology is one of those fascinating yet somewhat unsettling innovations of our time. In simple terms, deepfakes are realistic-looking fake videos or audio recordings where it appears that someone is saying or doing something they never actually did. This is done by using powerful machine learning algorithms—basically, computers that learn patterns and can mimic them.

The term “deepfake” first came into the spotlight in 2017. It started with a Reddit user who went by the name “deepfakes.” This user used AI to swap celebrities’ faces into existing videos, particularly in inappropriate or pornographic content, which understandably caused a lot of concern. The technology has since evolved and spread, and while it can be used for fun or artistic purposes, it also has a darker side.

How is a deepfake different from Photoshop or Faceswap? 

Let’s be honest, we’ve all had a bit of fun with those apps that swap our faces or show us how we’ll look when we’re older. They’re harmless, right? We can easily tell they’re fake. But here’s the kicker: before deepfakes came along, people used Photoshop and face-swapping to create misleading images and damage reputations. So, how does deepfake tech stack up against these old tricks? Let’s break it down and see why deepfakes are a whole different ball game. 

Here’s a simple comparison to help you understand the differences between deepfakes and more traditional techniques like face swaps or Photoshop.

Aspect	Deepfakes	Face Swaps/Photoshop
Technology Used	Machine learning and AI to create realistic videos or audio	Manual editing or basic software tools to change images
Realism	Extremely realistic; often hard to detect	Depends on skill level; usually noticeable
Effort Required	Requires large amounts of data (images, videos) and processing power	Can be done with less data and simpler tools
Application	Mostly used in videos to make it look like someone said or did something	Mainly used in images or short videos for fun or artistic purposes
Potential Harm	High; can spread misinformation or damage reputations	Lower, but can still be misleading or deceptive

What is the purpose of Creating Deep Fake?

We’ve all witnessed various controversies sparked by deepfakes. This technology, much like a double-edged sword, has both beneficial and harmful uses. With the rise of hyper-realistic fake videos, the reasons behind creating deep fakes range from harmless fun to downright sinister. Last March, the head of a UK branch of a German energy company transferred nearly £200,000 to a Hungarian bank account after a fraudster, pretending to be the German CEO, called him on the phone.

While some people use deepfakes for satire or entertainment, others exploit them to deceive and cause harm. As deepfake technology evolves, understanding its uses and potential risks becomes increasingly important.

Pornographic Content: 

Shockingly, according to stats 96% of deepfake videos found online by September 2019 were pornographic. Nearly all of these videos involved mapping the faces of female celebrities onto pornographic actors, highlighting a disturbing trend.

Revenge Porn: 

As deepfake technology becomes easier to use, even by those with minimal skills, there is a growing fear that fake videos will be used to target everyday people, especially women, as a form of revenge porn. This has led experts like Danielle Citron from Boston University to warn that “deepfake technology is being weaponized against women.”

Spoof and Satire: 

Beyond harmful uses, deepfakes are also created for spoofing, satire, and general mischief, showing that this technology can be used for both entertainment and more malicious purposes. One TikTok account under the name of Unreal Keanu Reeves is all about deepfakes featuring Keanu Reeves, with videos that mix everything from funny romantic scenarios to trending TikTok dances.

How to Create Deep Fakes Using Deep Fake Technology?

Making deepfakes is now as simple as making a TikTok video. In early 2023, a chic deepfake photo of the Pope sporting a stylish, knee-length Balenciaga puffer jacket went viral like wildfire. Thanks to modern technology, you don’t need to be a tech whiz to get it done. Here’s how it works: you just need to download the right software onto your laptop. 

Once you have it installed, you can use it to create videos that look incredibly real. Whether you want to make a funny clip or something more serious, the process is straightforward. It’s like having your own mini movie studio right at your fingertips, making it easy to create high-quality videos from the comfort of your home.

Here’s a simple step-by-step guide to creating deep fake videos:

1. Gather thousands of images of the two people you want to swap faces between.
2. Run these images through an AI algorithm called an encoder, which finds similarities between the faces and compresses them into shared features.
3. Use a second AI algorithm called a decoder. Train one decoder to recover the first person’s face from the compressed images, and another decoder to recover the second person’s face.
4. Feed the compressed image of person A into the decoder trained on person B. This will reconstruct person B’s face with person A’s expressions and orientation.
5. For a video, repeat the face swap process for every frame to create a convincing deepfake.
6. Alternatively, you can use Generative Adversarial Networks GANs, which involve two AI algorithms. One generates synthetic images, while the other distinguishes between real and fake images. Through repeated cycles, the generator improves until it produces highly realistic fake images or videos.

 Different Deep Fake Software and Apps:

We’ve all come across those hilarious Instagram reels and TikTok videos that seem too good to be true. With AI tech shaking things up, tons of apps and software now let you whip up deepfakes in minutes, all without burning a hole in your wallet.

 It’s like having a magic wand for your videos; just download the app and let the fun begin. Here’s a rundown of the top 10 deepfake software and apps that are making waves worldwide.

Name	Paid or Free	Pros
DeepFaceLab	Free	User-friendly interface, powerful algorithms, face swapping, facial expression manipulation, voice cloning.
FaceSwap	Free	Advanced facial recognition, versatile editing tools, customization options.
DeepArt	Paid	Transforms images into stunning artwork using deep learning algorithms.
Deepfake Studio	Paid	Intuitive interface, professional-quality video creation, powerful editing tools.
FakeApp	Free	Flexible features for beginners and experienced users, face swapping, voice synthesis.
DeepFaceLab GO	Free	Simplified interface, retains advanced features, ideal for beginners.
DeepArt Effects	Paid	Vast library of artistic filters and effects for videos and images.
FaceSwap Live	Paid	Real-time face swapping during video calls, fun and interactive.
DeepFace	Paid	Sophisticated facial recognition, seamless face integration in media.
FakeMe	Free	User-friendly, built-in templates, quick and easy deepfake content creation.

How to Spot Videos Created with Deepfake Technology:

As AI and technology zoom ahead faster than a speeding bullet, it’s becoming harder to tell what’s real and what’s fake. The line between the two is getting blurrier every day.  Some dedicated researchers and organizations are working around the clock to create top-notch tools and software to protect us from the sneaky side of this tech.  

In 2022, Google stopped people from using their Colab service to create deepfakes, which was a popular way to train these models. By 2024, YouTube now requires creators to tell viewers when their content is made using synthetic media or generative AI, including when it features real people’s likenesses. Also, starting in 2024, Meta will begin tagging AI-generated images on Facebook, Instagram, and Threads using industry-standard labels.

Even so, you can still catch those fake videos and photos if you’ve got a sharp eye or the right software. 

Spot Deep Fake Manually Without the Help of Software:

• Look for jerky or unnatural facial expressions and movements that don’t match the context of the video.
• Check for mismatched lighting on the face and surroundings. Deepfakes often struggle with realistic light consistency.
• Notice if the eyes appear unnatural, such as irregular blinking patterns or lack of eye movement.
• Pay attention to whether the audio syncs properly with the lip movements. Deepfakes sometimes have misaligned audio.
• Observe the skin texture and details. Deepfakes may have inconsistent skin smoothness or abnormal textures.
• Look for visual artifacts or areas of blurriness, especially around the edges of the face or hair.
• Watch for awkward or inconsistent body movements that don’t align with natural behavior.
• Check the background for distortions or anomalies, as deepfake technology can sometimes produce odd distortions.
• Always verify the authenticity of the content by checking the source and cross-referencing with reliable information.

Spot Deep Fake Using Online Software and Tools:

Here’s a handy list of software tools you can use to spot fake videos and images. These tools are designed to help you uncover whether visual content is real or if it’s been digitally altered. Whether you’re a casual viewer or a digital detective, these options can give you an edge in separating fact from fiction. 

Deepware Scanner

• Pros:
  • Detects AI-generated manipulations in videos.
  • Available as a web platform, RESTful API, and SDK.
  • User-friendly interface for video scanning.
• Cons:
  • Limited to videos up to 10 minutes long.
  • Requires separate steps for API and SDK versions.
• How to Use: Upload video URL to the web interface, or use API/SDK to scan and retrieve results.

DuckDuckGoose

• Pros:
  • Comprehensive suite including voice, text, and image/video detection.
  • Provides detailed explanations of manipulations.
  • Offers browser extensions and demo versions.
• Cons:
  • Some tools may require integration with existing systems.
  • Free tools may have limitations.
• How to Use: Use respective tools for specific content types or integrate with existing systems via API.

Google SynthID

• Pros:
  • Embeds invisible watermarks into AI-generated content.
  • Detectable by SynthID even after modifications.
  • Supports images, videos, and audio.
• Cons:
  • Currently available only to certain Vertex AI customers.
  • May not be widely accessible yet.
• How to Use: Embed SynthID watermark into AI-generated content for easy identification.

Intel FakeCatcher

• Pros:
  • Identifies authentic human markers within videos.
  • Operates with Intel hardware for high performance.
  • Real-time analysis with deep learning.
• Cons:
  • Requires Intel-specific hardware and software.
  • May not be suitable for all users.
• How to Use: Use the web-based platform to upload videos and receive authenticity reports.

Reality Defender

• Pros:
  • Detects deepfakes in images, videos, and audio.
  • Includes tools for text, voice, and document detection.
  • Offers real-time scanning and detailed reporting.
• Cons:
  • Comprehensive features may be complex for some users.
  • Enterprise-level solution may be costly.
• How to Use: Use the web application or API for scanning various media types and obtain detailed reports.

Sensity

• Pros:
  • Detects face swaps, manipulated audio, and AI-generated images.
  • Supports KYC processes and third-party integrations.
  • Offers a broad range of forensic checks.
• Cons:
  • May require integration with other platforms.
  • Can be complex for non-technical users.
• How to Use: Implement SDK or API for integrating deepfake detection into existing systems.

Sentinel

• Pros:
  • High accuracy in detecting deepfakes using advanced AI and neural networks.
  • Provides detailed visualization of detected manipulations.
  • Quick and easy-to-use workflow.
• Cons:
  • May be more suited for government and defense use.
  • Requires media upload for detection.
• How to Use: Upload media via the platform or API, receive analysis, and view results.

WeVerify Deepfake Detector

• Pros:
  • Decentralized platform with blockchain-based verification.
  • Analyzes both images and videos with detailed probability scores.
  • Integrates with content management systems.
• Cons:
  • May be complex for non-technical users.
  • Limited to specific content types and platforms.
• How to Use: Analyze media via the platform or plugin, receive probability scores, and use API for integration.

Conclusion:

With the ability to create incredibly convincing fake videos, audio, and images, it’s no wonder people are on high alert.

Fortunately, there’s a whole toolkit of deepfake detectors ready to help us out. From platforms that scan videos like a high-tech security guard to tools that embed sneaky watermarks in AI-generated content, we’ve got the means to keep things real. Each tool has its own special powers, whether it’s spotting a fake face, cracking a phony voice, or checking out suspicious text.